The effect of sprinkler and smoke barrier facilities on fire evacuation in apartment buildings
Bibliographic record
Abstract
Fire safety in high-rise residential buildings remains a critical challenge due to increasing urbanization and occupancy density. This study investigates the gap in quantifying synergistic interactions between sprinklers and smoke barriers, a topic underexplored in performance-based fire codes. Using an integrated framework combining Pyrosim and Pathfinder, this research models an apartment building under multiple fire scenarios, including corridor and adjacent room ignitions. Key parameters such as CO, visibility, and temperature are analysed to evaluate the effectiveness of standalone and combined fire protection measures. Results demonstrate that sprinklers alone extend the available safe egress time at Safety Exit 1 from 92 s to 154 s, while smoke barriers increased it to 115 s. The combined use of sprinklers and 60 cm smoke barriers with 5 m spacing achieves an available safe egress time of 420 s, effectively extends the time for personnel to escape. The combined utilization of firefighting facilities with strategic adjustment of smoke flow pathways under varied fire scenarios at different locations effectively prevents the hazard threshold from being reached throughout the 500-second simulation window. This study’s novelty lies in its parametric quantification of multi-measure synergies and practical guidelines for optimizing smoke barrier configurations. The findings directly inform revisions to fire codes and provide actionable strategies for designers and policymakers to enhance evacuation safety in high-rises. By bridging the gap between numerical modelling and real-world implementation, this research advances performance-based fire safety engineering, offering scalable solutions for global urban resilience.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".